Blockchain and Deep Learning for Smart Healthcare

Blockchain and Deep Learning for Smart Healthcare

by Akansha Singh, Anuradha Dhull, Krishna Kant Singh
Released January 2024
Publisher(s): Wiley-Scrivener
ISBN: 9781119791744

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Book description

BLOCKCHAIN and DEEP LEARNING for SMART HEALTHCARE

The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare.

The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare.

Audience

Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading.

Table of contents

  1. Cover
  2. Table of Contents
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Preface
  7. Part 1: Blockchain Fundamentals and Applications
    1. 1 Blockchain Technology: Concepts and Applications
      1. 1.1 Introduction
      2. 1.2 Blockchain Types
      3. 1.3 Consensus
      4. 1.4 How Does Blockchain Work?
      5. 1.5 Need of Blockchain
      6. 1.6 Uses of Blockchain
      7. 1.7 Evolution of Blockchain
      8. 1.8 Blockchain in Ethereum
      9. 1.9 Advantages of Smart Contracts
      10. 1.10 Use Cases of Smart Contracts
      11. 1.11 Real-Life Example of Smart Contracts
      12. 1.12 Blockchain in Decentralized Applications
      13. 1.13 Decentraland
      14. 1.14 Challenges Faced by Blockchain
      15. 1.15 Weaknesses of Blockchain
      16. 1.16 Future of Blockchain
      17. 1.17 Conclusion
      18. References
    2. 2 Blockchain with Federated Learning for Secure Healthcare Applications
      1. 2.1 Introduction
      2. 2.2 Federated Learning
      3. 2.3 Motivation
      4. 2.4 Federated Machine Learning
      5. 2.5 Federated Learning Frameworks
      6. 2.6 FL Perspective for Blockchain and IoT
      7. 2.7 Federated Learning Applications
      8. 2.8 Limitations
      9. References
    3. 3 Futuristic Challenges in Blockchain Technologies
      1. 3.1 Introduction
      2. 3.2 Blockchain
      3. 3.3 Issues and Challenges with Blockchain
      4. 3.4 Internet of Things (IoT)
      5. 3.5 Background of IoT
      6. 3.6 Conclusion
      7. References
    4. 4 AIML-Based Blockchain Solutions for IoMT
      1. 4.1 Introduction
      2. 4.2 Objective and Contribution
      3. 4.3 Security Challenges in Different Domains
      4. 4.4 Healthcare
      5. 4.5 Agriculture
      6. 4.6 Transportation
      7. 4.7 Smart Grid
      8. 4.8 Smart City
      9. 4.9 Smart Home
      10. 4.10 Communication
      11. 4.11 Security Attacks in IoT
      12. 4.12 Solutions for Addressing Security Using Machine Learning
      13. 4.13 Solutions for Addressing Security Using Artificial Intelligence
      14. 4.14 Solutions for Addressing Security Using Blockchain
      15. 4.15 Summary
      16. 4.16 Critical Analysis
      17. 4.17 Conclusion
      18. References
    5. 5 A Blockchain-Based Solution for Enhancing Security and Privacy in the Internet of Medical Things (IoMT) Used in e-Healthcare
      1. 5.1 Introduction: E-Health and Medical Services
      2. 5.2 Literature Review
      3. 5.3 Architecture of Blockchain-Enabled IoMT
      4. 5.4 Proposed Methodology
      5. 5.5 Conclusion and Future Work
      6. References
    6. 6 A Review on the Role of Blockchain Technology in the Healthcare Domain
      1. 6.1 Introduction
      2. 6.2 Systematic Literature Methodology
      3. 6.3 Applications of Blockchain in the Healthcare Domain
      4. 6.4 Blockchain Challenges
      5. 6.5 Future Research Directions and Perspectives
      6. 6.6 Implications and Conclusion
      7. References
    7. 7 Blockchain in Healthcare: Use Cases
      1. 7.1 Introduction
      2. 7.2 Challenges Faced in the Healthcare Sector
      3. 7.3 Use Cases of Blockchains in the Healthcare Sector
      4. 7.4 What is Medicalchain?
      5. 7.5 Implementing Blockchain in SCM
      6. 7.6 Why Use Blockchain in SCM
      7. References
  8. Part 2: Smart Healthcare
    1. 8 Potential of Blockchain Technology in Healthcare, Finance, and IoT: Past, Present, and Future
      1. 8.1 Introduction
      2. 8.2 Types of Blockchain
      3. 8.3 Literature Review
      4. 8.4 Methodology and Data Sources
      5. 8.5 The Application of Blockchain Technology Across Various Industries
      6. 8.6 Conclusion
      7. References
    2. 9 AI-Enabled Techniques for Intelligent Transportation System for Smarter Use of the Transport Network for Healthcare Services
      1. 9.1 Introduction
      2. 9.2 Artificial Intelligence
      3. 9.3 Artificial Intelligence: Transport System and Healthcare
      4. 9.4 Artificial Intelligence Algorithms
      5. 9.5 AI Workflow
      6. 9.6 AI for ITS and e-Healthcare Tasks
      7. 9.7 Intelligent Transportation, Healthcare, and IoT
      8. 9.8 AI Techniques Used in ITS and e-Healthcare
      9. 9.9 Challenges of AI and ML in ITS and e-Healthcare
      10. 9.10 Conclusions
      11. References
    3. 10 Classification of Dementia Using Statistical First-Order and Second-Order Features
      1. 10.1 Introduction
      2. 10.2 Materials and Methods
      3. 10.3 Proposed Framework
      4. 10.4 Experimental Results and Discussion
      5. 10.5 Conclusion
      6. References
    4. 11 Pulmonary Embolism Detection Using Machine and Deep Learning Techniques
      1. 11.1 Introduction
      2. 11.2 The State-of-the-Art of PE Detection Models
      3. 11.3 Literature Survey
      4. 11.4 Publications Analysis
      5. 11.5 Conclusion
      6. References
    5. 12 Computer Vision Techniques for Smart Healthcare Infrastructure
      1. 12.1 Introduction
      2. 12.2 Literature Survey
      3. 12.3 Proposed Idea
      4. 12.4 Results
      5. 12.5 Conclusion
      6. References
    6. 13 Energy-Efficient Fog-Assisted System for Monitoring Diabetic Patients with Cardiovascular Disease
      1. 13.1 Introduction
      2. 13.2 Literature Review
      3. 13.3 Architectural Design of the Proposed Framework
      4. 13.4 Fog Services
      5. 13.5 Smart Gateway and Fog Services Implementation
      6. 13.6 Cloud Servers
      7. 13.7 Experimental Results
      8. 13.8 Future Directions
      9. 13.9 Conclusion
      10. References
    7. 14 Medical Appliances Energy Consumption Prediction Using Various Machine Learning Algorithms
      1. 14.1 Introduction
      2. 14.2 Literature Review
      3. 14.3 Methodology
      4. 14.4 Machine Learning Algorithms Used
      5. 14.5 Results and Analysis
      6. 14.6 Model Analysis
      7. 14.7 Conclusion and Future Work
      8. References
  9. Part 3: Future of Blockchain and Deep Learning
    1. 15 Deep Learning-Based Smart e-Healthcare for Critical Babies in Hospitals
      1. 15.1 Introduction
      2. 15.2 Literature Survey
      3. 15.3 Evaluation Criteria
      4. 15.4 Results
      5. 15.5 Conclusion and Future Scope
      6. References
    2. 16 An Improved Random Forest Feature Selection Method for Predicting the Patient's Characteristics
      1. 16.1 Introduction
      2. 16.2 Literature Survey
      3. 16.3 Dataset
      4. 16.4 Data Analysis
      5. 16.5 Data Pre-Processing
      6. 16.6 Feature Selection Methods
      7. 16.7 Variable Importance by Machine Learning Methods
      8. 16.8 Random Forest Feature Selection
      9. 16.9 Proposed Methodology
      10. 16.10 Results and Discussion
      11. 16.11 Conclusion
      12. References
    3. 17 Blockchain and Deep Learning: Research Challenges, Open Problems, and Future
      1. 17.1 Introduction
      2. 17.2 Research Challenges
      3. 17.3 Open Problems
      4. 17.4 Future Possibilities
      5. 17.5 Conclusion
      6. References
  10. Index
  11. End User License Agreement

Product information

  • Title: Blockchain and Deep Learning for Smart Healthcare
  • Author(s): Akansha Singh, Anuradha Dhull, Krishna Kant Singh
  • Release date: January 2024
  • Publisher(s): Wiley-Scrivener
  • ISBN: 9781119791744